Role of CD19 Chimeric Antigen Receptor T Cell Therapy in Idiopathic Inflammatory Myopathies
Bibliographic record
Abstract
Idiopathic inflammatory myopathies (IIMs) comprise a spectrum of autoinflammatory disease characterized primarily by muscle inflammation, with secondary involvement of diverse organs including joints, skin, lungs, heart, and the gastrointestinal system. Managing these conditions poses considerable challenges, often inflicting profound distress on the afflicted individuals. Encouragingly, the deployment of chimeric antigen receptor (CAR) T cell therapy has demonstrated promising efficacy across various autoimmune diseases, extending hope for ameliorating the burden of IIM. This review provides an overview of the role of B cells in IIM pathogenesis, currently available B cell-depleting therapies, reasons for their lack of efficacy, and the application of CD19 CAR T cell therapy in the management of IIM, encompassing indications, efficacy, and tolerability profiles in these patient populations. Through this comprehensive review, we propose clinical trial design, target population, response criteria, and long-term follow-up measures for future clinical trials focusing on CD19 CAR T cell therapy in IIM. This overview aims to streamline research efforts and enhance the efficacy of therapeutic interventions in challenging cases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".